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I am having issues with plotly express in Jupyter notebook. The colors in the plot are faded and do not match the colors in the legend, which they are supposed to look like. Does anyone have any suggestions? Happy to provide more info, but I am not sure what would be useful - I am still new to Python.
fig = px.bar(funded_apps_mask_kewt, x='Grant Expended CY Quarter', y='Grant
Expended Amount', color='AMI Status',title='Long-Form Input')
fig.update_xaxes(categoryorder='category ascending')
fig.show()
AMI Statu | Grant Exp | Grant Exp Q | Grant Exp Q | Grant Exp Year | Grant Exp QY
0 Very Low (50%) 20086.72 Q4 2020 Q4 2020 2020 Q4
1 Urgent Need (120%)20086.7 Q4 2020 Q4 2020 2020 Q4
2 Urgent Need (120%)20086.72 Q4 2020 Q4 2020 2020 Q4
3 Very Low (50%) 20086.72 Q4 2020 Q4 2020 2020 Q4
4 Low (80%) 20086.72 Q4 2020 Q4 2020 2020 Q4
5 Low (80%) 20086.72 Q4 2020 Q4 2020 2020 Q4
6 Low (80%) 20086.72 Q4 2020 Q4 2020 2020 Q4
82Low (80%) 35602.75 Q1 2021 Q1 2021 2021 Q1
This is what my data looks like. I changed the column names so they could fit, but the columns I used are 'AMI Status', 'Grant Exp', and 'Grant Exp QY'. It has ~7K rows.
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Comparing Graph Objects and Plotly Express More complex figures such as sunbursts, parallel coordinates, facet plots or animations require many more lines of figure-specific graph objects code, whereas switching from one representation to another with Plotly Express usually involves changing just a few characters.
Plotly Express is really cool. I would 100% recommend using it for exploratory data analysis. The interactivity of the plots allows you to do a much more thorough investigation of your data with ease.
Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.
Each plotly trace type is primarily rendered with either SVG or WebGL, although WebGL-powered traces also use some SVG.
This is because of the bar outline, which can be removed by setting the marker.line.width attribute to 0:
fig.update_traces(dict(marker_line_width=0))
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